Azure 认知服务浅尝:徒然学会了抗拒热闹,却还来不及透悟真正的冷清；写个聊天机器人治愈自己吧

写在前面

• 之前上学使用华为的ModelArts平台做了类似的图像识别之类的小项目，零编码，但是需要自己搞数据集，标注、选择算法、训练模型等，用的话直接调API。
• NLP方面之前的一个实习公司有用，对一些类似招股书文件数据进行核查的。那会我作为Java开发做些数据清洗的工作，调NLP的接口去识别一些表格,然后用java写一些逻辑，把数据的按要求分类整理上传。
• 在之后工作中没有接触过，也没有学习过，但是对这方面蛮感兴趣的。基本算是小白，对NLP之类的算法也不懂，买了一本相关的书籍，也落灰了。看到这个活动，想学习学习，所以参加了。
• 依旧，附上活动链接：https://bbs.csdn.net/topics/601636817

活动内容：使用Azure认知服务免费提供的AI服务（包括语音转文本、文本转语音、语音翻译、文本分析、文本翻译、语言理解）开发智能应用，并以博文形式分享使用上述服务（至少试用3项服务）教程以及自己的使用心得体验；

我徒然学会了抗拒热闹，却还来不及透悟真正的冷清。--------张大春

在使用之前我们需要先了解下相关概念

一、关于认知服务的一些基本概念和术语

什么是 Azure 认知服务？：

二、什么是语言理解 (LUIS)？

1）、服务构建步骤

1、创建一个资源

使用Azure门户创建新资源
关于Azure 认知服务入门方面的教程，小伙伴可以移步官方文档 https://docs.azure.cn/zh-cn/cognitive-services/cognitive-services-apis-create-account?tabs=multiservice%2Cwindows

2、服务应用构建

步骤
登录到LUIS门户
创建新应用
生成模型
添加意向，即你要说些什么话，即语料，这个随便写点
添加13-15个
添加实体
使用预构建的模型，这里我们全都选择了,上面的2步应该就是生成这个，类似模板
训练模型
发布模型
查看信息

3、发布应用服务测试,使用python脚本调用接口

########### Python 3.6 ##############
# This quickstart shows how to predict the intent of an utterance by using the LUIS REST APIs.
# 导入模块
import requeststry:########### Values to modify.# YOUR-APP-ID: The App ID GUID found on the www.luis.ai Application Settings page.# 替换为自己的APP-IDappId = '949d3538-07df-4149-bee8-83dc7f4e11bd'# YOUR-PREDICTION-KEY: Your LUIS prediction key, 32 character value.prediction_key = '24440ef2829c45f0**61599ee00b496a'# YOUR-PREDICTION-ENDPOINT: Replace with your prediction endpoint.# For example, "https://westus.api.cognitive.microsoft.com/"prediction_endpoint = 'https://chatbot0.cognitiveservices.azure.cn/'# The utterance you want to use.# 你想和他说的话..utterance = '一个人怎么生活？'########### The headers to use in this REST call.headers = {}# The URL parameters to use in this REST call.params ={'query': utterance,'timezoneOffset': '0','verbose': 'true','show-all-intents': 'true','spellCheck': 'false','staging': 'false','subscription-key': prediction_key}# Make the REST call.response = requests.get(f'{prediction_endpoint}luis/prediction/v3.0/apps/{appId}/slots/production/predict', headers=headers, params=params)# Display the results on the console.print(response.json())except Exception as e:# Display the error string.print(f'{e}')

这里我们用docker搞一个python环境，然后执行一下脚本，测试一下

┌──[root@liruilongs.github.io]-[/liruilong]
└─$ docker pull centos/python-36-centos7
┌──[root@liruilongs.github.io]-[/liruilong]
└─$ ls
input  luis_run.sh  output  predict.py
┌──[root@liruilongs.github.io]-[/liruilong]
└─$ docker run --rm -it  --name=chatbot -v $PWD/predict.py:/predict.py centos/python-36-centos7  /bin/bash
(app-root) cd /
(app-root) ls
anaconda-post.log  bin  boot  dev  etc  help.1  home  lib  lib64  media  mnt  opt  predict.py  proc  root  run  sbin  srv  sys  tmp  usr  var
(app-root) python predict.py
Traceback (most recent call last):File "predict.py", line 6, in <module>import requests
ModuleNotFoundError: No module named 'requests'
(app-root) pip install requests
.........................
Collecting requestsDownloading https:/.....
(app-root) python predict.py
{'query': '一个人怎么生活？', 'prediction':{'topIntent': '生活加油', 'intents': {'生活加油': {'score': 0.8969882}, 'Calendar.ShowNext': {'score': 0.58274937}, 'Calendar.FindCalendarWhen': {'score': 0.25383785}, 'Places.GetReviews': {'score': 0.24764298}, 'Utilities.ReadAloud': {'score': 0.20971665}, 'HomeAutomation.QueryState': {'score': 0.15509635}, 'Calendar.CheckAvailability': {'score': 0.12212229}, 'Places.GetPriceRange': {'score': 0.122063436},........

测试成功 :predict.py脚本

2）、本地部署服务，启动和运行

1、 LUIS环境准备

进入资源
按照部署要求一步步构建
拉取镜像
最好找个镜像加速器配置一下，要不太慢了

2、安装并运行 LUIS 的 Docker 容器

运行步骤
必需的参数:所有认知服务容器都需要三个主要参数。 最终用户许可协议 (EULA) 的值必须为 accept。 此外，终结点URL和API密钥都是必需的。

运行 LUIS 的 Docker 容器

┌──[root@liruilongs.github.io]-[/liruilong]
└─$ mkdir input output
┌──[root@liruilongs.github.io]-[/liruilong]
└─$ ls
input  luis_run.sh  output
┌──[root@liruilongs.github.io]-[/liruilong]
└─$ cat luis_run.sh
docker run --rm -it -p 5000:5000 --memory 4g --cpus 2 -v $PWD/input:/input -v $PWD/output:/output mcr.microsoft.com/azure-cognitive-services/language/luis Eula=accept Billing=https://chatbot0.cognitiveservices.azure.cn/ ApiKey=24440ef2829c45f0**61599ee00b496a  ##这里参数填自己的
┌──[root@liruilongs.github.io]-[/liruilong]
└─$ docker run --rm -it -p 5000:5000 --memory 4g --cpus 2 -v $PWD/input:/input -v $PWD/output:/output mcr.microsoft.com/azure-cognitive-services/language/luis Eula=accept Billing=https://chatbot0.cognitiveservices.azure.cn/ ApiKey=24440ef2829c45f0a**1599ee00b496a  ## 启动容器EULA Notice: Copyright © Microsoft Corporation 2020. This Cognitive Services Container image is made available to you under the terms [https://go.microsoft.com/fwlink/?linkid=2018657] governing your subscription to Microsoft Azure Services (including the Online Services Terms [https://go.microsoft.com/fwlink/?linkid=2018760]). If you do not have a valid Azure subscription, then you may not use this container.Using '/input' for reading models and other read-only data.
Using '/output/luis/ff2a18ee78a1' for writing logs and other output data.
Logging to console.
Submitting metering to 'https://chatbot0.cognitiveservices.azure.cn/'.
warn: Microsoft.AspNetCore.DataProtection.KeyManagement.XmlKeyManager[35]No XML encryptor configured. Key {d826e89b-febe-4b93-bad8-db07cb994012} may be persisted to storage in unencrypted form.
warn: Microsoft.AspNetCore.Server.Kestrel[0]Overriding address(es) 'http://+:80'. Binding to endpoints defined in UseKestrel() instead.
Hosting environment: Production
Content root path: /app
Now listening on: http://0.0.0.0:5000
Application started. Press Ctrl+C to shut down.

测试
查看接口API

应用包上传，放到input文件夹下

┌──(liruilong㉿Liruilong)-[/mnt/c/Users/lenovo/Downloads]
└─$ scp ./949d3538-07df-4149-bee8-83dc7f4e11bd_production.gz  root@192.168.26.55:/
949d3538-07df-4149-bee8-83dc7f4e11bd_production.gz                                    100% 6434KB  19.0MB/s   00:00

放到input文件夹下，启动容器

┌──[root@liruilongs.github.io]-[/]
└─$ cp 949d3538-07df-4149-bee8-83dc7f4e11bd_production.gz  /liruilong/input/
┌──[root@liruilongs.github.io]-[/]
└─$ cd /liruilong/input/
┌──[root@liruilongs.github.io]-[/liruilong/input]
└─$ ls
949d3538-07df-4149-bee8-83dc7f4e11bd_production.gz
┌──[root@liruilongs.github.io]-[/liruilong/input]
└─$ cd ..
┌──[root@liruilongs.github.io]-[/liruilong]
└─$ pwd
/liruilong
┌──[root@liruilongs.github.io]-[/liruilong]
└─$ # 启动容器服务┌──[root@liruilongs.github.io]-[/liruilong]
└─$ docker run --rm --name=demo  -it -p 5000:5000 --memory 4g --cpus 2 -v $PWD/input:/input -v $PWD/output:/output mcr.microsoft.com/azure-cognitive-services/language/luis Eula=accept Billing=https://chatbot0.cognitiveservices.azure.cn/ ApiKey=24440ef2829c45f0a**1599ee00b496aEULA Notice: Copyright © Microsoft Corporation 2020. This Cognitive Services Container image is made available to you under the terms [https://go.microsoft.com/fwlink/?linkid=2018657] governing your subscription to Microsoft Azure Services (including the Online Services Terms [https://go.microsoft.com/fwlink/?linkid=2018760]). If you do not have a valid Azure subscription, then you may not use this container.Using '/input' for reading models and other read-only data.
Using '/output/luis/da43b9631f9d' for writing logs and other output data.
Logging to console.
Submitting metering to 'https://chatbot0.cognitiveservices.azure.cn/'.
warn: Microsoft.AspNetCore.DataProtection.KeyManagement.XmlKeyManager[35]No XML encryptor configured. Key {886021ff-6bf5-423d-be12-ba9b52383b9e} may be persisted to storage in unencrypted form.
warn: Microsoft.AspNetCore.Server.Kestrel[0]Overriding address(es) 'http://+:80'. Binding to endpoints defined in UseKestrel() instead.
Hosting environment: Production
Content root path: /app
Now listening on: http://0.0.0.0:5000
Application started. Press Ctrl+C to shut down.

文件名不对，需要改一下
用swagger测试一下

随便找一句测试一下：

据悉，该活动由世界休闲组织，杭州市政府主办，中国国际科技促进会三农发展工作委员会等联合会承办。

{"query": "据悉，该活动由世界休闲组织，杭州市政府主办，中国国际科技促进会三农发展工作委员会等联合会承办。","topScoringIntent": {"intent": "Places.GetPhoneNumber","score": 0.9103095},"entities": [{"entity": "工作","type": "Calendar.Subject","startIndex": 35,"endIndex": 36,"score": 0.63087225},{"entity": "际科技促进会三农发展工作委员会等联合会承办 。","type": "Note.Text","startIndex": 25,"endIndex": 46,"score": 0.6798551},{"entity": "杭州市","type": "Places.AbsoluteLocation","startIndex": 14,"endIndex": 16,"score": 0.966151536},{"entity": "国际科","type": "Places.PlaceName","startIndex": 24,"endIndex": 26,"score": 0.3605822},{"entity": "工作","type": "Calendar.DestinationCalendar","startIndex": 35,"endIndex": 36,"resolution": {"values": ["工作"]}},{"entity": "工作","type": "Places.OpenStatus","startIndex": 35,"endIndex": 36,"resolution": {"values": ["工作"]}},{"entity": "休闲","type": "RestaurantReservation.Atmosphere","startIndex": 9,"endIndex": 10,"resolution": {"values": ["休闲"]}}]
}

回过头看看语言理解的定义：

语言理解 (LUIS) 是一种基于云的对话式 AI 服务，可在用户对话的自然语言文本中应用自定义机器学习智能，以便预测整体含义并提炼出相关的详细信息。 LUIS 通过其自定义门户、API 和 SDK 客户端库提供访问权限。找重点，会提炼出相关信息，换句话讲，就是把要表达的信息转化成机器或者说AI能够识别的信息。

简单尝试一下，可以把生成的实体组合，作为关键字给类似图灵机器人用，进行简单对话，简单测试了下，发现效果很一般,可能方法不太对，或者我找的机器人太差了，Azure的机器人需要注册绑卡…所以这个以后有时间研究研究

---

额…聊天机器人没出写来,唐突了，没法治愈自己了 ^ _ ^

下面看看其他的认知服务，语音合成产品系列，我们现在聊天大都是语音，对于聊天机器人来说，需要把语音转化为文本。然后才是语言理解。

三、什么是语音转文本？

1)、服务构建：

1、创建一个资源

创建一个资源

2) JAVA开发环境准备，拉去github的Demo

这里我们使用过java的方式

Git ：https://github.com/Azure-Samples/cognitive-services-speech-sdk/tree/master/quickstart/java/jre/from-microphone

步骤
克隆代码
导入项目

3）调用API测试

调用API测试
语音文件转文本
找了一首 梁静茹-我还记得 歌曲测试下，发现不行，可能还没这么智能,或者歌词太长了
麦克风转文本：大城小爱中的一句歌词识别：是妈妈告诉我的哲理 ===》妈妈告诉我，我的心里。应该是歌曲的原因，正常说话可以还是不错的，这里调硬件的代码直接封装好了，特别方便

package speechsdk.quickstart;import com.microsoft.cognitiveservices.speech.*;
import com.microsoft.cognitiveservices.speech.audio.AudioConfig;import java.util.concurrent.ExecutionException;
import java.util.concurrent.Future;
import java.util.concurrent.Semaphore;import static com.microsoft.cognitiveservices.speech.ResultReason.*;/*** @Classname Program* @Description TODO* @Date 2021/10/30 13:58* @Created LiRuilong*/
public class Program {private static Semaphore stopTranslationWithFileSemaphore;public static void main(String[] args) throws InterruptedException, ExecutionException {SpeechConfig speechConfig = SpeechConfig.fromSubscription("eb48f918a90448fe***53633d6301ebb", "chinanorth2");speechConfig.setSpeechRecognitionLanguage("zh-cn");// 从文件中识别// SpeechRecognitionResult result =  fromFile(speechConfig);// 从麦克风识别SpeechRecognitionResult result =  fromMic(speechConfig);switch (result.getReason()) {case RecognizedSpeech:System.out.println("We recognized: " + result.getText());break;case NoMatch:System.out.println("NOMATCH: 无法识别语音.");break;case Canceled: {CancellationDetails cancellation = CancellationDetails.fromResult(result);System.out.println("CANCELED: Reason=" + cancellation.getReason());if (cancellation.getReason() == CancellationReason.Error) {System.out.println("CANCELED: ErrorCode=" + cancellation.getErrorCode());System.out.println("CANCELED: ErrorDetails=" + cancellation.getErrorDetails());System.out.println("CANCELED: Did you update the subscription info?");}}default:{};break;}}/*** @param speechConfig:* @return: void* @Description  从麦克风识别* @author LiRui long* @date  2021/11/1  18:30**/public static SpeechRecognitionResult  fromMic(SpeechConfig speechConfig) throws InterruptedException, ExecutionException {AudioConfig audioConfig = AudioConfig.fromDefaultMicrophoneInput();SpeechRecognizer recognizer = new SpeechRecognizer(speechConfig, audioConfig);System.out.println("对这麦克风说话.");Future<SpeechRecognitionResult> task = recognizer.recognizeOnceAsync();SpeechRecognitionResult result = task.get();return  result;}/*** @param speechConfig:* @return: com.microsoft.cognitiveservices.speech.SpeechRecognitionResult* @Description          从文件中识别* @author LiRui long* @date  2021/11/1  18:29**/public static SpeechRecognitionResult fromFile(SpeechConfig speechConfig) throws InterruptedException, ExecutionException {AudioConfig audioConfig = AudioConfig.fromWavFileInput("E:\\docker\\cognitive-services-speech-sdk\\quickstart\\java\\jre\\translate-speech-to-text\\src\\speechsdk\\quickstart\\梁静茹-我还记得.wav");SpeechRecognizer recognizer = new SpeechRecognizer(speechConfig, audioConfig);// First initialize the semaphore.stopTranslationWithFileSemaphore = new Semaphore(0);recognizer.recognizing.addEventListener((s, e) -> {System.out.println("RECOGNIZING: Text=" + e.getResult().getText());});recognizer.recognized.addEventListener((s, e) -> {if (e.getResult().getReason() == RecognizedSpeech) {System.out.println("RECOGNIZED: Text=" + e.getResult().getText());}else if (e.getResult().getReason() == NoMatch) {System.out.println("NOMATCH: Speech could not be recognized.");}});recognizer.canceled.addEventListener((s, e) -> {System.out.println("CANCELED: Reason=" + e.getReason());if (e.getReason() == CancellationReason.Error) {System.out.println("CANCELED: ErrorCode=" + e.getErrorCode());System.out.println("CANCELED: ErrorDetails=" + e.getErrorDetails());System.out.println("CANCELED: Did you update the subscription info?");}stopTranslationWithFileSemaphore.release();});recognizer.sessionStopped.addEventListener((s, e) -> {System.out.println("\n    Session stopped event.");stopTranslationWithFileSemaphore.release();});Future<SpeechRecognitionResult> task = recognizer.recognizeOnceAsync();SpeechRecognitionResult result = task.get();return  result;//System.out.println("RECOGNIZED: Text=" + result.getText());}}

四、什么是文本翻译

1)、服务构建：

创建资源

2）Node环境调用API测试

这里我们用node环境来测试一下;

$ docker pull node
$ mkdir translateDemo;cd translateDemo
$ vim translateDemo.js

测试js准备

const axios = require('axios').default;
const { v4: uuidv4 } = require('uuid');let subscriptionKey = "3c6588c7026b41a4**7f81551cb4a737";
let endpoint = "https://api.translator.azure.cn/";let location = "chinanorth";axios({baseURL: endpoint,url: '/translate',method: 'post',headers: {'Ocp-Apim-Subscription-Key': subscriptionKey,'Ocp-Apim-Subscription-Region': location,'Content-type': 'application/json','X-ClientTraceId': uuidv4().toString()},params: {'api-version': '3.0','from': 'zh-Hans','to': ['zh-Hant', 'en']},data: [{'text': '我徒然学会了抗拒热闹，却还来不及透悟真正的冷清。--------张大春'}],responseType: 'json'
}).then(function(response){console.log(JSON.stringify(response.data, null, 4));
})

这里测试将 【我徒然学会了抗拒热闹，却还来不及透悟真正的冷清。--------张大春】中文简体翻译为中文繁体，英语。

┌──[root@liruilongs.github.io]-[~/translateDemo]
└─$ vim translateDemo.js
┌──[root@liruilongs.github.io]-[~/translateDemo]
└─$ docker run -it --rm --name=translateDemo -v $PWD/translateDemo.js:/root/translateDemo.js node:latest /bin/bash
root@35376c1c05d8:/# pwd
/
root@35376c1c05d8:/# cd root/;npm install axios uuidadded 3 packages, and audited 4 packages in 7s1 package is looking for fundingrun `npm fund` for detailsfound 0 vulnerabilities
root@35376c1c05d8:~# node translateDemo.js
[{"translations": [{"text": "我徒然學會了抗拒熱鬧，卻還來不及透悟真正的冷清。 --------張大春","to": "zh-Hant"},{"text": "I learned in vain to resist the excitement, but it is too late to understand the real cold. -------- Zhang Dachun","to": "en"}]}
]
root@35376c1c05d8:~#

时间原因，关于Azure认知服务免费提供的AI服务就尝试到这里，聊天机器人没有写出来哈，但是对Azure认知服务有一些了解，嘻，生活加油 ^ _ ^